Control strategies for redundant robots subject to multiple tasks constraints

Supervisor:

ROCCO PAOLO

Thesis abstract:

In recent years, interest in the use of redundant robot manipulators to accomplish multiple tasks has been constantly increasing, also in the industrial environment. The opportunities offered by the redundant degrees of freedom, sometimes augmented exploiting mobile bases, would allow robots to complete their main task while complying with other constraints (e.g. collision and self-collision avoidance, singularity avoidance, safety constraints, productivity constraints, etc.). All of this would make it easier for robots to work close to humans in a destructured environment, increasing production flexibility.
The aim of this research is to devise a control architecture that takes into account all of the constraints simultaneously imposed to a (possibly mobile) redundant robot, developing a redundancy resolution strategy that assures the satisfaction of multiple tasks with different priority and that is interfaced online with the low-level control. The online planning and resolution would also allow a dynamical adaptation to changes both in the tasks and in the environment, known for instance through exteroceptive sensors.